小红书音视频策略算法工程师
社招全职3-5年内容理解地点:北京状态:招聘
任职要求
任职资格 1、本科及以上学历,计算机、软件工程、数学等相关专业; 2.、熟悉至少一种常用机器学习模型/算法框架(PyTorch/Tensorflow/Scikit-learn 等),有强化学习和大模型应用相关经验优先; 3、具有较强的自驱力,有冲劲,成长诉求强烈,具备出色的沟通能力和跨部门团队协作能力; 4、对技术有追求,跟进前沿的相关技术并应用,有ACL/EMNLP/SIGIR/KDD/CIKM等相关顶会论文优先。
工作职责
工作职责 1、负责小红书音点直播、图片内容的全链路用户消费体验优化,主导策略框架的迭代与升级,包括选档位策略优化等,持续提升用户体验; 2、负责精细化设计不同场景的转码、下发,为用户提供端到端的个性化体验(画质与流畅) 3、深度参与以用户消费体验为核心的策略优化项目,通过AB实验、因果推断、强化学习及大模型等数据驱动与算法手段,精准定位业务痛点,推动关键指标提升与业务落地。
包括英文材料
学历+
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
PyTorch+
https://datawhalechina.github.io/thorough-pytorch/
PyTorch是利用深度学习进行数据科学研究的重要工具,在灵活性、可读性和性能上都具备相当的优势,近年来已成为学术界实现深度学习算法最常用的框架。
https://www.youtube.com/watch?v=V_xro1bcAuA
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
TensorFlow+
https://www.youtube.com/watch?v=tpCFfeUEGs8
Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
https://www.youtube.com/watch?v=ZUKz4125WNI
This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.
Scikit-learn+
https://www.ibm.com/think/topics/scikit-learn
Scikit-learn, or sklearn, is an open source project and one of the most used machine learning (ML) libraries today.
https://www.youtube.com/watch?v=SIEaLBXr0rk
Today we to a crash course on Scikit-Learn, the go-to library in Python when it comes to traditional machine learning algorithms (i.e., not deep learning).
强化学习+
https://cloud.google.com/discover/what-is-reinforcement-learning?hl=en
Reinforcement learning (RL) is a type of machine learning where an "agent" learns optimal behavior through interaction with its environment.
https://huggingface.co/learn/deep-rl-course/unit0/introduction
This course will teach you about Deep Reinforcement Learning from beginner to expert. It’s completely free and open-source!
https://www.kaggle.com/learn/intro-to-game-ai-and-reinforcement-learning
Build your own video game bots, using classic and cutting-edge algorithms.
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
相关职位
校招策略算法
1、参与核心策略设计与实现:深入小红书音视频、直播、图片等内容的分发与体验优化全链路,参与转码、下发、消费等核心策略的设计、编码与迭代,并且可以设计清晰、可扩展的技术方案,并通过高质量的代码实现它; 2、有数据挖掘和数据分析能力,并且可以在真实的业务场景中,学习并运用AB实验、因果推断等科学方法评估策略效果。同时探索强化学习、大模型等前沿技术在用户体验优化领域的应用可能。
更新于 2025-10-17
实习J1001
1 挖掘海量用户数据,进行音视频场景的画像体系建设,包括但不限于机型画像、网络画像、用户清晰度/流畅度偏好画像等,精准刻画用户音视频属性。 2. 建设音视频体验QoE模型,优化播放和边缘计算相关策略,如预加载、CDN调度、PCDN等; 3. 基于因果模型、机器学习模型等框架进行音视频用户画像研发,全链路优化模型效果,包括特征优化,模型结构优化等 4. 与内外部团队合作,包括商业化、电商等,制定基于用户价值的体验和成本ROI优化策略,并推动优化上线。
更新于 2025-03-04
校招J1001
1、负责音视频点播、直播领域核心策略算法的设计与优化,包括视频转码策略(基于内容感知的自适应视频处理和编码- CAE、档位Ladder设计等)、传输和播放策略(自适应多码率-ABR、缓存策略、后处理等),为用户提供端到端的个性化播放体验,平衡清晰度、流畅度与成本; 2、挖掘海量线上数据,通过机器学习、因果推断等方法建立主播、视频、用户粒度的画像模型,精细化控制算法策略,推动时长/营收等核心指标提升; 3、与内外部团队合作,制定面向不同业务(主站/电商/商业化/海外等)的优化策略,主导算法设计、验证、工程落地、AB实验全流程,推动算法上线。
更新于 2025-08-12